Evaluation of how different implementation strategies of an injury prevention programme (FIFA 11+) impact team adherence and injury risk in Canadian female youth football players: a cluster-randomised trial
Bibliographic record
Abstract
BACKGROUND: Injury prevention programme delivery on adherence and injury risk, specifically involving regular supervisions with coaches and players on programme execution on field, has not been examined. AIM: The objective of this cluster-randomised study was to evaluate different delivery methods of an effective injury prevention programme (FIFA 11+) on adherence and injury risk among female youth football teams. METHOD: During the 4-month 2011 football season, coaches and 13-year-old to 18-year-old players from 31 tier 1-3 level teams were introduced to the 11+ through either an unsupervised website ('control') or a coach-focused workshop with ('comprehensive') and without ('regular') additional supervisions by a physiotherapist. Team and player adherence to the 11+, playing exposure, history and injuries were recorded. RESULTS: Teams in the comprehensive and regular intervention groups demonstrated adherence to the 11+ programme of 85.6% and 81.3% completion of total possible sessions, compared to 73.5% for teams in the control group. These differences were not statistically significant, after adjustment for cluster by team, age, level and injury history. Compared to players with low adherence, players with high adherence to the 11+ had a 57% lower injury risk (IRR 0.43, 95% CI 0.19 to 1.00). However, adjusting for covariates, this between-group difference was not statistically significant (IRR=0.44, 95% CI 0.18 to 1.06). CONCLUSION: Following a coach workshop, coach-led delivery of the FIFA 11+ was equally successful with or without the additional field involvement of a physiotherapist. Proper education of coaches during an extensive preseason workshop was more effective in terms of team adherence than an unsupervised delivery of the 11+ programme to the team. TRIAL REGISTRATION: ISRCTN67835569.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".